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Jay T. Runkel

dblp:45/2363 · DBLP profile ↗
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4ranked-venue papers
2as first author
0since 2021 · last 1996
—ORCID · none

Domains — the database's venue-derived domains; a paper can count in several

Human-computer interaction and ubiquitous computing · 3 · 1 first-authorArtificial intelligence and machine learning · 1 · 1 first-authorGraphics, computer vision, multimedia, augmented reality and games · 1 · 1 first-author

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Artificial intelligence
3 papers
Knowledge representation and reasoning · 100%
Human-computer interaction and pervasive computing
1 paper
Design research and methods · 100%
Software engineering, system software, and programming languages
1 paper
Requirements engineering and software design · 100%

Topics — the 7 heaviest of 8, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Knowledge, reasoning and agents › Knowledge representation and reasoning
ontology
0.021996
The configuration design ontologies and the VT elevator domain theory · Int. J. Hum. Comput. Stud. 1996
Solving VT by reuse · Int. J. Hum. Comput. Stud. 1996
Knowledge, reasoning and agents › Knowledge representation and reasoning › model-based reasoning
propose-and-revise
0.011996
Solving VT by reuse · Int. J. Hum. Comput. Stud. 1996
Knowledge, reasoning and agents › Knowledge representation and reasoning
knowledge acquisition
0.011994
Building Non-Brittle Knowledge-Acquisition Tools · AAAI 1994
Knowledge, reasoning and agents › Knowledge representation and reasoning › knowledge acquisition
knowledge-acquisition tools
0.011994
Building Non-Brittle Knowledge-Acquisition Tools · AAAI 1994
Design research and methods › design knowledge
design rationale
0.011994
Solving Sisyphus by design · Int. J. Hum. Comput. Stud. 1994
Knowledge, reasoning and agents › Knowledge representation and reasoning › domain knowledge
domain theory
0.011996
The configuration design ontologies and the VT elevator domain theory · Int. J. Hum. Comput. Stud. 1996
Requirements engineering and software design
knowledge-based design
0.011994
Building Non-Brittle Knowledge-Acquisition Tools · AAAI 1994

Methods — techniques the papers use, named apart from their topics

ontology engineering · 0.0knowledge acquisition · 0.0knowledge reuse · 0.0design case study · 0.0
YearPublicationVenuePosition
1996 The configuration design ontologies and the VT elevator domain theory
abstract
In the VT/Sisyphus experiment, a set of problem solving systems were being built against a common specification of a problem. An important hypothesis was that the specification could be given, in large part, as a common ontology. This article is that ontology. This ontology is different than normal software specification documents in two fundamental ways. First, it is formal and machine readable (i.e. in the KIF/Ontolingua syntax). Second, the descriptions of the input and output of the task to be performed include domain knowledge (i.e. about elevator configuration) that characterize semantic constraints on possible solutions, rather than describing the form (data structure) of the answer. The article includes an overview of the conceptualization, excerpts from the machine-readable Ontolingua source files, and pointers to the complete ontology library available on the Internet.
Thomas R. Gruber, Gregory R. Olsen, Jay T. Runkel
Int. J. Hum. Comput. Stud.3
1996 Solving VT by reuse
Jay T. Runkel, William P. Birmingham, Alan Balkany
Int. J. Hum. Comput. Stud.1
1994 Building Non-Brittle Knowledge-Acquisition Tools
Jay T. Runkel, William P. Birmingham
AAAI1
1994 Solving Sisyphus by design
Alan Balkany, William P. Birmingham, Jay T. Runkel
Int. J. Hum. Comput. Stud.3